de.lmu.ifi.dbs.elki.algorithm.clustering

Class Leader<O>

java.lang.Object

de.lmu.ifi.dbs.elki.algorithm.AbstractAlgorithm<R>

de.lmu.ifi.dbs.elki.algorithm.AbstractDistanceBasedAlgorithm<O,Clustering<PrototypeModel<O>>>

de.lmu.ifi.dbs.elki.algorithm.clustering.Leader<O>

Type Parameters:

O - Object type

All Implemented Interfaces:

Algorithm, ClusteringAlgorithm<Clustering<PrototypeModel<O>>>, DistanceBasedAlgorithm<O>

@Reference(authors="J. A. Hartigan",
           title="Chapter 3: Quick Partition Algorithms, 3.2 Leader Algorithm",
           booktitle="Clustering algorithms",
           url="http://dl.acm.org/citation.cfm?id=540298",
           bibkey="books/wiley/Hartigan75/C3")
public class Leader<O>
extends AbstractDistanceBasedAlgorithm<O,Clustering<PrototypeModel<O>>>
implements ClusteringAlgorithm<Clustering<PrototypeModel<O>>>

Leader clustering algorithm.

Reference:

J. A. Hartigan
Clustering algorithms, Chapter 3, Quick Partition Algorithms

This implementation does not use the linear process described, but uses index structures. This may or may not be faster.

TODO: when no index is available, fall back to the original approach.

Since:

0.7.5

Author:

Erich Schubert

Nested Class Summary

Nested Classes

Modifier and Type	Class and Description
static class	Leader.Parameterizer<O> Parameterization class.

Field Summary

Fields

Modifier and Type	Field and Description
private static Logging	LOG Class logger.
private double	threshold Maximum distance from leading object,

Fields inherited from class de.lmu.ifi.dbs.elki.algorithm.AbstractAlgorithm

ALGORITHM_ID

Fields inherited from interface de.lmu.ifi.dbs.elki.algorithm.DistanceBasedAlgorithm

DISTANCE_FUNCTION_ID

Constructor Summary

Constructors

Constructor and Description
Leader(DistanceFunction<? super O> distanceFunction, double threshold) Constructor.

Method Summary

Modifier and Type	Method and Description
TypeInformation[]	getInputTypeRestriction() Get the input type restriction used for negotiating the data query.
protected Logging	getLogger() Get the (STATIC) logger for this class.
Clustering<PrototypeModel<O>>	run(Relation<O> relation) Run the leader clustering algorithm.

Methods inherited from class de.lmu.ifi.dbs.elki.algorithm.AbstractDistanceBasedAlgorithm

getDistanceFunction

Methods inherited from class de.lmu.ifi.dbs.elki.algorithm.AbstractAlgorithm

run

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Methods inherited from interface de.lmu.ifi.dbs.elki.algorithm.clustering.ClusteringAlgorithm

run

Field Detail

threshold

private double threshold

Maximum distance from leading object,

LOG

private static final Logging LOG

Class logger.

Constructor Detail

Leader

public Leader(DistanceFunction<? super O> distanceFunction,
              double threshold)

Constructor.

Parameters:

distanceFunction - Distance function

threshold - Maximum distance from leading object

Method Detail

run

public Clustering<PrototypeModel<O>> run(Relation<O> relation)

Run the leader clustering algorithm.

Parameters:

relation - Data set

Returns:

Clustering result

getInputTypeRestriction

public TypeInformation[] getInputTypeRestriction()

Description copied from class: AbstractAlgorithm

Get the input type restriction used for negotiating the data query.

Specified by:

getInputTypeRestriction in interface Algorithm

Specified by:

getInputTypeRestriction in class AbstractAlgorithm<Clustering<PrototypeModel<O>>>

Returns:

Type restriction

getLogger

protected Logging getLogger()

Description copied from class: AbstractAlgorithm

Get the (STATIC) logger for this class.

Specified by:

getLogger in class AbstractAlgorithm<Clustering<PrototypeModel<O>>>

Returns:

the static logger